Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas

被引:0
作者
Zhen Liu
Xuanke Hong
Linglong Wang
Zeyu Ma
Fangzhan Guan
Weiwei Wang
Yuning Qiu
Xueping Zhang
Wenchao Duan
Minkai Wang
Chen Sun
Yuanshen Zhao
Jingxian Duan
Qiuchang Sun
Lin Liu
Lei Ding
Yuchen Ji
Dongming Yan
Xianzhi Liu
Jingliang Cheng
Zhenyu Zhang
Zhi-Cheng Li
Jing Yan
机构
[1] The First Affiliated Hospital of Zhengzhou University,Department of Neurosurgery
[2] Yanjing Medical College of Capital Medical University,Department of Pathology
[3] The First Affiliated Hospital of Zhengzhou University,Department of MRI
[4] The First Affiliated Hospital of Zhengzhou University,Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology
[5] Chinese Academy of Sciences,undefined
[6] University of Chinese Academy of Sciences,undefined
[7] China-Japan Union Hospital of Jilin University,undefined
[8] Shenzhen United Imaging Research Institute of Innovative Medical Equipment,undefined
来源
BMC Cancer | / 23卷
关键词
Pediatric low-grade glioma; Magnetic resonance imaging; Radiomics; Machine learning; fusion;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas
    Liu, Zhen
    Hong, Xuanke
    Wang, Linglong
    Ma, Zeyu
    Guan, Fangzhan
    Wang, Weiwei
    Qiu, Yuning
    Zhang, Xueping
    Duan, Wenchao
    Wang, Minkai
    Sun, Chen
    Zhao, Yuanshen
    Duan, Jingxian
    Sun, Qiuchang
    Liu, Lin
    Ding, Lei
    Ji, Yuchen
    Yan, Dongming
    Liu, Xianzhi
    Cheng, Jingliang
    Zhang, Zhenyu
    Li, Zhi-Cheng
    Yan, Jing
    BMC CANCER, 2023, 23 (01)
  • [2] Predicting IDH Mutation Status in Low-Grade Gliomas Based on Optimal Radiomic Features Combined with Multi-Sequence Magnetic Resonance Imaging
    He, Ailing
    Wang, Peng
    Zhu, Aihua
    Liu, Yankui
    Chen, Jianhuan
    Liu, Li
    DIAGNOSTICS, 2022, 12 (12)
  • [3] Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers
    Haldar, Debanjan
    Kazerooni, Anahita Fathi
    Arif, Sherjeel
    Familiar, Ariana
    Madhogarhia, Rachel
    Khalili, Nastaran
    Bagheri, Sina
    Anderson, Hannah
    Shaikh, Ibraheem Salman
    Mahtabfar, Aria
    Kim, Meen Chul
    Tu, Wenxin
    Ware, Jefferey
    Vossough, Arastoo
    Davatzikos, Christos
    Storm, Phillip B.
    Resnick, Adam
    Nabavizadeh, Ali
    NEOPLASIA, 2023, 36
  • [4] Applications of machine learning to MR imaging of pediatric low-grade gliomas
    Kudus, Kareem
    Wagner, Matthias
    Ertl-Wagner, Birgit Betina
    Khalvati, Farzad
    CHILDS NERVOUS SYSTEM, 2024, 40 (10) : 3027 - 3035
  • [5] Deriving quantitative information from multiparametric MRI via Radiomics: Evaluation of the robustness and predictive value of radiomic features in the discrimination of low-grade versus high-grade gliomas with machine learning
    Ubaldi, Leonardo
    Saponaro, Sara
    Giuliano, Alessia
    Talamonti, Cinzia
    Retico, Alessandra
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2023, 107
  • [6] Radiomic features on multiparametric MRI for differentiating pseudoprogression from recurrence in high-grade gliomas
    Lin, Jie
    Su, Chun-Qiu
    Tang, Wen-Tian
    Xia, Zhi-Wei
    Lu, Shan-Shan
    Hong, Xun-Ning
    ACTA RADIOLOGICA, 2024, 65 (11) : 1390 - 1400
  • [7] Radiomic Prediction of CCND1 Expression Levels and Prognosis in Low-grade Glioma Based on Magnetic Resonance Imaging
    Zhao, Kun
    Zhang, Hui
    Lin, Jianyang
    Xu, Shoucheng
    Liu, Jianzhi
    Qian, Xianjing
    Gu, Yongbing
    Ren, Guoqiang
    Lu, Xinyu
    Chen, Baomin
    Chen, Deng
    Yan, Jun
    Ma, Jichun
    Wei, Wenxiang
    Wang, Yuanwei
    ACADEMIC RADIOLOGY, 2024, 31 (11) : 4595 - 4610
  • [8] Molecular subtype classification of low-grade gliomas using magnetic resonance imaging-based radiomics and machine learning
    Lam, Luu Ho Thanh
    Do, Duyen Thi
    Diep, Doan Thi Ngoc
    Nguyet, Dang Le Nhu
    Truong, Quang Dinh
    Tri, Tran Thanh
    Thanh, Huynh Ngoc
    Le, Nguyen Quoc Khanh
    NMR IN BIOMEDICINE, 2022, 35 (11)
  • [9] Functional magnetic resonance imaging-guided resection of low-grade gliomas
    Hall, WA
    Liu, HY
    Truwit, CL
    SURGICAL NEUROLOGY, 2005, 64 (01): : 20 - 27
  • [10] Molecular genetics and therapeutic targets of pediatric low-grade gliomas
    Tateishi, Kensuke
    Nakamura, Taishi
    Yamamoto, Tetsuya
    BRAIN TUMOR PATHOLOGY, 2019, 36 (02) : 74 - 83